1. Machine learning classification of resting state functional connectivity predicts smoking status. We applied support vector machine (SVM)-based classification to resting state functional connectivity (rsFC) data from nicotine-dependent smokers and healthy controls to identify brain-based features predictive of nicotine dependence. By employing a network-centered approach, we observed that within-network rsFC measures offered maximal information for predicting smoking status, as opposed to between-network connectivity, or the representativeness of each individual node with respect to its parent network. Further, that connectivity measures within the executive control and frontoparietal networks are particularly informative in predicting smoking status. Our findings suggest that machine learning-based approaches to classifying rsFC data offer a valuable technique to understand large-scale differences in addiction-related neurobiology. 2. Early life stress interacts with monoaminergic genes to enhance risk for nicotine addiction. Individuals who possess certain monoaminergic gene alleles are more vulnerable to positive and negative environmental influences than others, with those who carry these susceptibility alleles and have experienced negative environmental factors will be at higher risk for psychological disorders, such as depression and ADHD. Due to the high rate of comorbidity between these disorders and smoking, we hypothesize a gene and environment interaction (GxE) effect on nicotine addiction such that individuals who carry certain susceptibility gene alleles and have faced negative environmental influences will be at higher risk of being a smoker. The five genes of interest were DRD2, DRD4, MAOA, SLC6A4, and HTR2A. Adversity was measured using the Childhood Trauma Questionnaire (CTQ). We found that individuals carrying susceptibility gene alleles had increased likelihood of being a smoker, and observed similar GxE effects on traits impulsivity and reward dependence. Our findings have strong implications for prevention and early intervention strategies for addiction. 3. Acute nicotine abstinence effects on craving and cognitive function predicted by large-scale brain network coupling. Cognitive dysfunction is a core component of neuropsychiatric and addictive disorders. Specific cognitive deficits in working memory (WM) emerge during nicotine withdrawal. Accompanying these deficits are reduced activation in executive control regions and less suppression in task-independent regions. These patterns of activity are also reflected in fluctuations in large-scale brain networks at rest. Nicotine enhances brain rsFC and functional efficiency of brain networks. Accumulative evidences suggests that the strength of between-network coupling appears to be a key determinant of cognitive abilities. We tested the hypothesis that the strength of coupling among three large-scale brain networks salience, executive control, and default mode will reflect the state of nicotine withdrawal and will predict abstinence-induced craving and cognitive deficit. We developed a resource allocation index (RAI) that reflects the combined strength of interactions among the three large-scale networks. The RAI was significantly lower in the abstinent versus smoking satiety states, suggesting weaker inhibition between the DMN and SN. Reduced RAI predicted abstinence-induced cravings to smoke and less suppression of DMN activity during performance of a WM task. Alterations in coupling of the SN and DMN and the inability to disengage from the DMN may be critical in cognitive/affective alterations that underlie nicotine dependence. 4. Differential Modulation of Reward Anticipation by Varenicline and Nicotine. Anticipatory reward processing is reduced in smokers. However, these deficits are mitigated by the administration of nicotine. To assess anticipatory reward processing, smokers and non-smokers performed a modified monetary incentive delay task including separate cues of valence and magnitude of rewards. Participants were administered order balanced varenicline and placebo then scanned under each condition wearing a nicotine or placebo patch. Reward cue processing yielded no evidence of the hypothesized interaction between varenicline and nicotine. Instead, varenicline reduced gain magnitude processing in smokers, while nicotine enhanced activation to reward-predicting cues in both groups. These findings are inconsistent with prior evidence of vareniclines action as a partial antagonist in affective processing, and suggest that vareniclines efficacy as a pharmacotherapy for smoking cessation may include differentiated mechanisms of action within distinct brain circuits for affective and reward processing. 5. Greater externalizing personality traits predict less error-related insula and anterior cingulate cortex activity in acutely abstinent cigarette smokers. Attenuated activity in performance-monitoring brain regions following erroneous actions may contribute to the repetition of maladaptive behaviors such as continued drug use. Externalizing is a broad personality construct characterized by deficient impulse control, vulnerability to addiction, and reduced neurobiological indices of error processing. The insula and dorsal anterior cingulate cortex (dACC) are critically linked with error processing as well as the perpetuation of cigarette smoking. As such, we examined the interrelations between externalizing tendencies, erroneous task performance, and error-related insula and dACC activity in overnight-deprived smokers and nonsmokers. We observed that higher externalizing tendencies correlated with the occurrence of more performance errors in smokers but not in nonsmokers. Suggesting a neurobiological contribution to such sub-optimal performance in smokers, higher externalizing also predicted less recruitment of the right insula and dACC following error commission. Given that inadequate error-related neuronal responses may contribute to continued drug use despite negative consequences, these results suggest that externalizing tendencies and/or compromised error processing in subsets of smokers may be relevant factors for smoking cessation success. 6. Neurobiological impact of nicotinic acetylcholine receptor stimulation: An ALE meta-analysis of pharmacological fMRI studies. Pharmacological stimulation of nicotinic acetylcholine receptors (nAChRs) augments cognition among smokers and nonsmokers, yet the underlying mechanisms are not fully understood. Aggregating the corpus of fMRI results regarding nicotinic agonists provides a means to identify common mechanisms by which nAChR stimulation exerts pro-cognitive effects. We conducted a meta-analysis of pharmacological neuroimaging studies within the activation likelihood estimation framework. When considering published studies contrasting a nAChR stimulation condition versus a baseline, nAChR stimulation was associated with convergent activity decreases in multiple regions, most notably the ventromedial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), and parahippocampus. Conversely, convergent activity increases were observed in lateral frontoparietal cortices, the dorsal anterior cingulate cortex (ACC), thalamus, and cuneus. These meta-analytic results suggest a common neurobiological mechanism by which nicotinic agonists enhance cognition and provide quantitative meta-analytic support for the systems-level perspective that nAChR stimulation suppresses activity in default mode network regions while enhancing activity in executive control network regions.